Intelligent management of computerized advanced processing

ABSTRACT

Systems and methods are disclosed for automatically managing how and when computerized advanced processing techniques (for example, CAD and/or other image processing) are used. In some embodiments, the systems and methods discussed herein allow users, such as radiologists, to efficiently interact with a wide variety of computerized advanced processing (“CAP”) techniques using computing devices ranging from picture archiving and communication system (“PACS”) workstations to handheld devices such as smartphone and tablets. Furthermore, the systems and methods may, in various embodiments, automatically manage how data associated with these CAP techniques (for example, results of application of one or more computerized advanced processing techniques) are used, such as how data associated with the computerized analyses is reported, whether comparisons to prior abnormalities should be automatically initiated, whether the radiologist should be alerted of important findings, and the like.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a divisional of U.S. patent application Ser. No.14/139,068, filed Dec. 23, 2013, which claims the benefit of priorityunder 35 U.S.C. § 119(e) of U.S. Provisional Application No. 61/750,662,filed Jan. 9, 2013, the disclosures of which are hereby incorporated byreference herein in their entireties.

BACKGROUND

In medical imaging, some exams are processed using computerized advancedprocessing, such as Computer Aided Diagnosis (CAD) systems, quantitativeanalysis (blood flow, volumetrics, image enhancement, etc.), or otherprocessing systems, for example. With continued progress in the fieldsof Artificial Intelligence, image processing, and image analysis, it isanticipated that the use of CAD and advanced processing will grow overtime and their use will become routine in the future.

SUMMARY

The systems, methods, and devices described herein each have severalaspects, no single one of which is solely responsible for its desirableattributes. Without limiting the scope of this disclosure, severalnon-limiting features will now be described briefly.

According to an embodiment, a computing system is disclosed thatcomprises: one or more hardware computer processors configured toexecute software instructions; and one or more electronic storagedevices in communication with the one or more hardware computerprocessors and storing software modules, the software modules comprisingsoftware instructions configured for execution by the one or morehardware computer processors in order to cause the computing system to:access, from one or more image storage devices, an image seriescomprising one or more medical images; determine an exam characteristicassociated with the image series, the exam characteristic including aresult of a previously run computerized advanced processing technique;access, from a computerized advanced processing data structure, rulesfor execution of respective computerized advanced processing techniques,the rules indicating: one or more associations between examcharacteristics and corresponding computerized advanced processingtechniques, the exam characteristics including at least a modality andexam type; and one or more criteria associated with respectivecomputerized advanced processing techniques for automatically initiatingexecution of corresponding computerized advanced processing techniques;determine, based on the rules, one or more computerized advancedprocessing techniques associated with the determined exam characteristicof the image series; and for each of the determined computerizedadvanced processing techniques: in response to determining that criteriaassociated with the computerized advanced processing technique aresatisfied, automatically initiate execution of the computerized advancedprocessing technique on the image series.

According to another embodiment, a computing system is disclosed thatcomprises: one or more hardware computer processors configured toexecute software instructions; and one or more electronic storagedevices in communication with the one or more hardware computerprocessors and storing software modules, the software modules comprisingsoftware instructions configured for execution by the one or morehardware computer processors in order to cause the computing system to:access, from one or more image storage devices, an image seriescomprising one or more medical images; determine an exam characteristicassociated with the image series; access a computerized advancedprocessing data structure including rules for executing respectivecomputerized advanced processing techniques based on corresponding examcharacteristics; identify one or more rules that are matched by the examcharacteristic; and initiate execution of computerized advancedprocessing techniques associated with the identified one or more rulesthat are matched by the exam characteristic.

According to yet another embodiment, a computing system is disclosedthat comprises: one or more hardware computer processors configured toexecute software instructions; and one or more electronic storagedevices in communication with the one or more hardware computerprocessors and storing software modules, the software modules comprisingsoftware instructions configured for execution by the one or morehardware computer processors in order to cause the computing system to:access, from one or more image storage devices, one or more image serieseach comprising one or more medical images; access a computerizedadvanced processing data structure including rules indicating respectivecomputerized advanced processing techniques available for respectivesubsets of characteristics associated with medical data; identify one ormore rules that are matched by characteristics of a particular one ormore image series; and generate a user interface for display to a user,the user interface including information regarding computerized advancedprocessing techniques associated with the identified one or more rulesthat are matched by characteristics of the particular one or more imageseries.

According to another embodiment, a computing system is disclosed thatcomprises: one or more hardware computer processors configured toexecute software instructions; and one or more electronic storagedevices in communication with the one or more hardware computerprocessors and storing software modules, the software modules comprisingsoftware instructions configured for execution by the one or morehardware computer processors in order to cause the computing system to:access, from one or more image storage devices, an image seriescomprising one or more medical images; determine a characteristicassociated with a first computerized advanced processing techniqueapplied to the image series; access a computerized advanced processingdata structure including rules for executing computerized advancedprocessing techniques based on characteristics of previously appliedcomputerized advanced processing techniques; identify a rule thatcorresponds to the determined characteristic associated with the firstcomputerized advanced processing technique, the rule indicatingexecution of a second computerized advanced processing technique; andinitiate application of the second computerized advanced processingtechnique to the image series.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1, 2, and 3 are system and block diagrams which show variousexample components of systems and computing devices for implementingvarious methods and processes of the present disclosure, according tovarious embodiments.

FIGS. 4A-4B are tables illustrating examples of rules that may be storedby systems of the present disclosure, according to various embodiments.

FIG. 4C is a flowchart illustrating an example process for runningcomputerized advanced processing automatically or manually, according toan embodiment of the present disclosure.

FIG. 5 illustrates an example user interface in which status informationis displayed, according to an embodiment of the present disclosure.

FIG. 6 illustrates an example user interface in which status informationand medical images with notations are displayed, according to anembodiment of the present disclosure.

FIGS. 7A-7B are flowcharts illustrating example processes ofcomputerized advanced processing, according to various embodiments ofthe present disclosure.

FIG. 8 is a flowchart illustrating another example process ofcomputerized advanced processing, according to an embodiment of thepresent disclosure.

DETAILED DESCRIPTION

Embodiments of the disclosure will now be described with reference tothe accompanying figures, wherein like numerals refer to like elementsthroughout. The terminology used in the description presented herein isnot intended to be interpreted in any limited or restrictive manner,simply because it is being utilized in conjunction with a detaileddescription of certain specific embodiments of the disclosure.Furthermore, embodiments of the disclosure may include several novelfeatures, no single one of which is solely responsible for its desirableattributes or which is essential to practicing the embodiments of thedisclosure herein described.

In various embodiments, systems and methods are disclosed forautomatically managing how and when computerized advanced processingtechniques (for example, CAD and/or other image processing) are used. Insome embodiments, the systems and methods discussed herein allow users,such as radiologists, to efficiently interact with a wide variety ofcomputerized advanced processing (“CAP”) techniques using computingdevices ranging from Picture Archiving and Communications System (PACS)workstations to handheld devices such as smartphone, tablets, or evensmart watches. Furthermore, the systems and methods may, in variousembodiments, automatically manage how data associated with these CAPtechniques (for example, results of application of one or morecomputerized advanced processing techniques) are used, such as how dataassociated with the computerized analyses is reported, whethercomparisons to prior abnormalities should be automatically initiated,whether the radiologist should be alerted of important findings, and thelike.

In order to facilitate an understanding of the systems and methodsdiscussed herein, certain terms may be defined in this document. Suchterms should be construed to include the provided definitions, theordinary and customary meaning of the terms, and/or any other impliedmeaning for the respective terms. Accordingly, any definitions providedherein do not limit the meaning of the defined terms, but only provideexemplary definitions.

The term CAP (computerized advanced processing), as use herein, shouldbe interpreted to cover one or more of the various computerized imageanalyses, image analysis techniques, and/or image processing techniquesdiscussed herein, and/or any similar computerized processing techniquesthat are currently or later available. CAP will be described herein withregard to radiology images, but CAP and the systems and methodsdescribed herein may be applied in other areas including, but notlimited to, other types of medical images (for example, cardiology,dermatology, pathology and/or endoscopy, among others), computergenerated images (for example, 3D images from virtual colonoscopy, 3Dimages of vessels from CTA, and the like), images from other fields (forexample, surveillance imaging, satellite imaging, and the like), as wellas non-imaging data including audio, text, and numeric data. In someembodiments, CAP may include, but is not limited to, volumetricrendering, multiplanar reconstruction (MPR), maximum intensityprojection (MIP), other image processing techniques, and the like.

Example Computing Systems

FIG. 1 is a system diagram which shows the various components of asystem 100 configured for managing and/or displaying informationutilizing certain systems and methods described herein, according tovarious embodiments. As shown, the system 100 may include a computingdevice 150 and may further include other systems, such as those shown inFIG. 1 and described below.

The computing device 150, also referred to herein as “device 150,” maytake various forms. In one embodiment, the computing device 150 may bean information display computing device, and/or a computer workstationhaving information display software modules 151. In other embodiments,software modules 151 may reside on another computing device, such as aweb server or other server, and a user directly interacts with a secondcomputing device that is connected to the web server via a computernetwork.

In one embodiment, the computing device 150 comprises one or morecomputing devices, such as a server, a desktop computer, a workstation,a laptop computer, a mobile computer, a smartphone, a tablet computer, acell phone, a personal digital assistant, a gaming system, a kiosk, anaudio player, and/or any other device that utilizes a graphical userinterface, such as office equipment, automobiles, airplane cockpits,household appliances, automated teller machines, self-service checkoutsat stores, information and other kiosks, ticketing kiosks, vendingmachines, industrial equipment, and/or a television, for example.

The computing device 150 may run an off-the-shelf operating system 154such as a Windows, Linux, MacOS, Android, or iOS. The computing device150 may also run a more specialized operating system which may bedesigned for the specific tasks performed by the computing device 150.

The computing device 150 may include one or more computer processors152, for example, hardware computer processors. The computer processors152 may include central processing units (CPUs), and may further includededicated processors such as graphics processor chips, or otherspecialized processors. The processors may be used to execute computerinstructions based on the modules 151 to cause the computing device toperform operations as specified by the modules 151. The modules 151 mayinclude, by way of example, components, such as software components,object-oriented software components, class components and taskcomponents, processes, functions, attributes, procedures, subroutines,segments of program code, drivers, firmware, microcode, circuitry, data,databases, data structures, tables, arrays, and variables. For example,modules may include software code written in a programming language,such as, for example, Java, JavaScript, ActionScript, Visual Basic,HTML, Lua, C, C++, or C#. While “modules” are generally discussed hereinwith reference to software, any modules may alternatively be representedin hardware or firmware. In various embodiments, the modules describedherein refer to logical modules that may be combined with other modulesor divided into sub-modules despite their physical organization orstorage.

The computing device 150 may also include memory 153. The memory 153 mayinclude volatile data storage such as RAM or SDRAM. The memory 153 mayalso include more permanent forms of storage such as a hard disk drive,a flash disk, flash memory, a solid state drive, or some other type ofnon-volatile storage.

The computing device 150 may also include or be interfaced to one ormore display devices 155 that provide information to users of thecomputing device. Display devices 155 may include a video display, suchas one or more high-resolution computer monitors, or a display deviceintegrated into or attached to a laptop computer, handheld computer,smartphone, computer tablet device, or medical scanner. In otherembodiments, the display device 155 may include an LCD, OLED, or otherthin screen display surface, a monitor, television, projector, a displayintegrated into wearable glasses, or any other device that visuallydepicts user interfaces and data to viewers.

The computing device 150 may also include or be interfaced to one ormore input devices 156 which receive input from users, such as akeyboard, trackball, mouse, 3D mouse, drawing tablet, joystick, gamecontroller, touch sensitive surface (for example, capacitive orresistive touch screen), touchpad, accelerometer, video camera and/ormicrophone.

The computing device 150 may also include one or more interfaces 157which allow information exchange between computing device 150 and othercomputers and input/output devices using systems such as Ethernet,Wi-Fi, Bluetooth, as well as other wired and wireless datacommunications techniques.

The modules of the computing device 150 may be connected using astandard based bus system. In different embodiments, the standard basedbus system could be Peripheral Component Interconnect (“PCI”), PCIExpress, Accelerated Graphics Port (“AGP”), Micro channel, SmallComputer System Interface (“SCSI”), Industrial Standard Architecture(“ISA”) and Extended ISA (“EISA”) architectures, for example. Inaddition, the functionality provided for in the components and modulesof computing device 150 may be combined into fewer components andmodules or further separated into additional components and modules.

The computing device 150 may communicate and/or interface with othersystems and/or devices. In one or more embodiments, the computer device150 may be connected to a computer network 190. The computer network 190may take various forms. For example, the computer network 190 may be awired network or a wireless network, or it may be some combination ofboth. The computer network 190 may be a single computer network, or itmay be a combination or collection of different networks and networkprotocols. Additionally, the computer network 190 may include one ormore local area networks (LAN), wide area networks (WAN), personal areanetworks (PAN), cellular or data networks, and/or the Internet.

Various devices and subsystems may be connected to the network 190. Forexample, one or more medical scanners may be connected, such as MRIscanners 120. The MRI scanner 120 may be used to acquire MRI images frompatients, and may share the acquired images with other devices on thenetwork 190. The network 190 may also include one or more CT scanners122. The CT scanners 122 may also be used to acquire images and, likethe MRI scanner 120, may then store those images and/or share thoseimages with other devices via the network 190. Any other scanner ordevice capable of inputting or generating information that can bepresented to the user as images, graphics, text or sound may beconnected to the network 190, including, for example, computing systemsused in the fields of ultrasound, angiography, nuclear medicine,radiography, endoscopy, pathology, dermatology, and the like.

Also connected to the network 190 may be a Picture Archiving andCommunications System (PACS) 136 and PACS workstation 138. The PACSSystem 136 may be used for the storage, retrieval, distribution andpresentation of images (such as those created and/or generated by theMRI scanner 120 and CT Scanner 122). The medical images may be stored inan independent format, an open source format, or some other proprietaryformat. A common format for image storage in the PACS system is theDigital Imaging and Communications in Medicine (DICOM) format. Invarious embodiments, the stored images may be transmitted digitally viathe PACS system, often reducing or eliminating the need for manuallycreating, filing, or transporting film jackets.

The network 190 may also be connected to a Radiology Information System(RIS) 140. In an embodiment, the radiology information system 140 may bea computerized system that is used by radiology departments to store,manipulate and distribute patient radiological information.

Also attached to the network 190 may be an Electronic Medical Record(EMR) system 142. The EMR system 142 may be configured to store and makeaccessible to a plurality of medical practitioners computerized medicalrecords. Also attached to the network 190 may be a LaboratoryInformation System 144. In an embodiment, the Laboratory InformationSystem 144 may be a software system which stores information created orgenerated by clinical laboratories. Also attached to the network 190 maybe a Digital Pathology System 146 that may be used to digitally manageand store information related to medical pathology.

Also attached to the network 190 may be one or more Computer AidedDiagnosis Systems (CAD) systems 148 (including CAD systems 148 a, 148 b,and/or any quantity of CAD systems) that are generally used to performCAP such as, for example, CAD processes. In one embodiment, the CADsystems 148 functionality may reside in a computing device separate fromcomputing device 150 while in another embodiment the CAD systems 148functionality may reside within computing device 150.

Also attached to the network 190 may be one or more Processing Systems149 (including Processing Systems 149 a, 149 b, and/or any quantity ofProcessing Systems) that may be used to perform CAP such as, forexample, computations on imaging information to create new views of theinformation, for example, 3D volumetric display, MultiplanarReconstruction (MPR), and Maximum Intensity Projection reconstruction(MIP), as well as other types of processing, for example imageenhancement, volume quantification, blood-flow quantification, and thelike. In one embodiment, such processing functionality may reside in acomputing device separate from computing device 150 while in anotherembodiment the Processing functionality may reside within computingdevice 150.

Also connected to the network 190 may be a Web Server 147.

In the embodiment of FIG. 1, a computerized advanced processing rulesdata structure 160 is also coupled to the network 190. The computerizedadvanced processing rules data structure may exist in a number of forms,for example as a table, file, database, and/or other electronic datastructure. The rules data structure 160 may include a listing ofcomputerized advanced processing (CAP) that are available for use, forexample by device 150. Particular CAP may be associated with variouscriteria, such as based on modality, description, patient information,clinical indication, medical facility, requesting doctor, imageattributes, series type or description, and the like. For example, oneor more CAP may be automatically selected for a particular image, seriesof images, and/or imaging exam (for example, which may include one ormore image series) based on attributes of an image, series of images,and/or imaging exam, among other attributes. An image series maycomprise one or more images. The rules data structure 160 may furtherinclude criteria for when certain CAP are automatically executed (forexample, before the exam is sent to the radiologist for review) and/orwhether confirmation is required before execution (for example, theradiologist may need to confirm that a particular CAP is performed). Therules data structure 160 may include rules for executing a particularCAP based on results of a first one or more CAP (that may have beenautomatically performed). Thus, in some embodiments multiple CAP may beselected and performed based on the various rules in the rules datastructure 160. In some embodiments, the rules may include user, usergroup, site, and/or other preferences for selection and/or execution ofCAP.

In the embodiment of FIG. 1, a computerized advanced processing (CAP)communication preferences data structure 160 is also coupled to thenetwork 190. In various embodiments the CAP communications preferencesdata structure may be a file, table, database, and/or other electronicstructure capable of holding communication preferences information. TheCAP communications preferences data structure may contain informationregarding how results of CAP are to be communicated. For example, someCAP results may be considered significant, as defined, for example, inCAP rules data structure 160. The CAP communications preferences maycontain information regarding how significant results should becommunicated (for example, differently than non-significant results).For example, a particular physician may indicate that certain types ofsignificant results are to be communicated to him automatically via hissmartphone, for example, using a push notification or text message. Inanother example, CAP communications preferences may specify that as soonas any CAP detects a significant result, that the results should beautomatically communicated to the radiologist on call via his pager sohe can immediately view the case, confirm the significance of the CAPresult, and contact the appropriate physician caring for the patient.

In other embodiments, other computing devices that store, provide,acquire, and/or otherwise manipulate medical data may also be coupled tothe network 190 and may be in communication with one or more of thedevices illustrated in FIG. 1, such as with the computing device 150.

Depending on the embodiment, devices other than the computing device 150that are illustrated in FIG. 1 may include some or all of the samecomponents discussed above with reference to the computing device 150.

FIG. 2 is a system diagram which shows various components of a system200, many of which are discussed above with reference to FIG. 1. In theexample of FIG. 2, several specific CAP are illustrated, includingvarious CAD processes (for example, CAD process 180 a, 180 b, 180 c, and180 d), and other processing (for example, stenosis measurement 182 a,dementia analysis 182 b, perfusion measurement 182 c, and volumequantification 182 d). Each of these processes may be associated with asoftware module that is executable by various computing devices, such asthe CAD systems 148, processing systems 149, the device 150, any otherdevice(s) illustrated in FIGS. 1, 2, and/or 3, and/or any other suitablecomputing device. The CAP rules data structure 160 may includeidentification information for each of the processes 180 and 182, suchas information on how each computerized advanced processing can beinitiated, such as hardware addresses for devices that perform eachprocess and/or identification information for the particular process(for example, that may be used to initiate a particular CAP, even ifmultiple CAP are performed by a single computing device). In otherembodiments other types of CAP may be utilized. In one embodiment, aninformation display computing device, such as computing device 150(FIG. 1) and/or computing device 250 (FIG. 3) may be in communicationwith any of the devices illustrated in FIG. 2 via the network 190.

FIG. 3 is a block diagram of another network configuration of acomputing device 250, which includes many of the same componentsdiscussed above with reference to computing device 150, and multiple CADand processing systems. In this particular configuration, the CAD system192 a and/or Processing system 190 a may be accessible to the computingdevice 250 via a local network 390, such as a secure local area network(for example, within a hospital or medical complex). The computingdevice may also access CAD system 192 b and/or processing system 190 bvia a wide area network (WAN) 392, such as the Internet. Access to theWAN 392 may include communication through the local network 390 or maybe directly between the computing device 250 and the WAN 392 in otherembodiments. In the example of FIG. 3, the computing device may alsoinclude a CAD system 192 c and processing system 190 c, such as in theform of software modules that are stored on the computing device 250 andexecutable by the computing device. In other embodiments, a computingdevice, such as computing device 250 may access CAP systems/modules thatare accessible in any one or more combinations of the above-notedmanners, such as directly (for example, stored on the computing device),via a local network (for example, a local server executes the CAPmodule), and/or via a wide area network (for example, a remote server iscontacted via the Internet and executes the CAP modules).

Example Rules for Selection of One or More Computerized AdvancedProcessing

FIG. 4A is a table illustrating an example of rules that may be storedin the CAP rules data structure 160 and/or otherwise accessed in orderto automatically determine one or more CAP to perform on an image, imageseries, and/or imaging exam. In this example, the table (which may beany other data structure in other embodiments) indicates associationsbetween particular modalities (column 402), exam types (column 404), andCAP (column 406) that may be valuable to examination of the exam images.The table further includes a rules column 408 that includes rules forexecution of the CAP indicated in column 406. The rules may indicatethat certain CAP are performed automatically (for example, without anyinput from the radiologist), automatically if certain conditions are met(for example, insurance covers, exam has certain characteristics,previous CAP has certain results, and the like), or after confirmationfrom a radiologist, for example. In the example rules 408, words inquotes indicate clinical indication or history, such as “trauma.” Therules may further include other criteria for executing one or more CAP,for example based on one or more of:

-   -   Which CAP systems are available    -   Exam characteristics, for example, MRI of spine vs. CT of brain    -   Clinical information, for example, brain MRI where clinical        question is dementia (one type of processing) vs. trauma        (another type of processing)    -   User preference    -   Site preference    -   Insurance approval    -   Billable status    -   Referring docs order    -   Presence of comparison exam    -   Whether or not a certain type of CAP was already performed on        the exam and/or on a prior exam, for example:        -   If prior exam used CAD, automatically compare to result.        -   If prior exam used Quantitative Analysis, automatically            compare to result.    -   Results of another CAP. For example, a rule may indicate that a        particular CAP should be run if another specific CAP had a        certain result (for example, another CAP had a result that was        abnormal, normal, demonstrated a particular finding,        demonstrated a measurement in a particular range, and/or the        like).    -   Status of another CAP. For example, a rule may indicate that two        CAP should be performed, but that a second CAP should not be        performed until the first CAP is complete. By way of example,        “Brain aneurysm detection CAD” may require that a “3D Vessel        tracking” CAP be run first, as “Brain aneurysm detection CAD”        may process the results of “3D Vessel tracking” CAP. The last        example rule listed in the example CAP Rules table of FIG. 4B        (described below) illustrates another example in which three CAP        are automatically run in a particular sequence in the event that        two conditions are met.

In some embodiments certain results of a CAP may automatically triggerthe scheduling of another CAP (for example, based on the rules in column408). For example, the modality and exam in rule 410 is associated withBrain MRI exams (as indicated in columns 402 and 404), and the indicatedCAP of “MRI brain volumetric analysis” is associated with a rule (column408) indicating that the CAP is automatically performed when theclinical indication is “dementia.”

In some embodiments, scheduling of a particular CAP, eitherautomatically or manually, may automatically cause one or more other CAPto be scheduled before or after that particular CAP. For example, examrule 412 indicates that scheduling of “Brain aneurysm detected CAD”should result in the automatic scheduling of “3D Vessel tracking” CAP,and that “3D Vessel tracking” CAP should be run before “Brain aneurysmdetected CAD”, for example because “Brain aneurysm detected CAD”involves processing the results of “3D Vessel tracking” CAP.

In another example, the modality and exam in rule 411 is associated withBrain MRI exams (as indicated in columns 402 and 404), and the indicatedCAP of “MRI brain CSF analysis” is associated with a rule (column 408)indicating that the CAP is automatically performed when the clinicalindication is “hydrocephalus,” “dementia,” or there is an abnormal brainvolumetric analysis from another CAP.

Thus, in an embodiment, the first CAP in rule 410 (“MRI Brain volumetricanalysis”) may first be automatically performed on a brain MRI, such asin response to an indication of “dementia” in the MRI order from thereferring doctor. Once the MRI brain volumetric analysis has beenperformed, the rules of FIG. 4A may again be applied to determine if oneor more additional CAP should be performed. In this example, if theresult of the MRI brain volumetric analysis is “abnormal” (or equivalentnomenclature), another CAP listed in rule 411 (MRI brain CSF analysis)is triggered for automated execution. Thus, in various embodiments, therules may be configured to initiate execution of multiple CAP inresponse to results of previously performed CAP.

In one embodiment, a rules data structure may be used to determine whichCAP are compatible and/or available for a particular one or more imageseries, such as based on various characteristics associated with the oneor more image series. For example, a rules data structure comprisingmodality, exam, and CAD/processing, such as columns 402, 404, and 406 inthe example of FIG. 4A, may be used to determine which of the variousCAD/processing are compatible with medical images in particular exammodalities and exams. In one embodiment, this information may bepresented to users. In the example of rows 410 and 411, “MRI brainvolume analysis” and “MRI brain CSF analysis” are listed as compatibleand/or available for MRI exams of the brain.

In various embodiments, different rules may apply to different usersand/or different user groups (for example, based on preferences of theusers and/or user groups).

FIG. 4B is a table illustrating an example of rules that may be storedin the CAP rules data structure 160 and/or otherwise accessed in orderto automatically determine one or more CAP to perform on an image orimage series.

In various embodiments, rules related to CAP may be evaluatedautomatically, for example when:

-   -   An exam is completed on a scanner.    -   An exam is communicated, for example, from a scanner to a PACS        System or from a PACS System to a PACS Workstation.    -   A CAP is performed, for example, such that the result of the CAP        may automatically trigger performance of another CAP.

In various embodiments, evaluation of rules related to CAP may beperformed on one or more computing devices, such as scanners, PACSSystems, PACS Workstations, and the like. Based on the evaluation ofrules related to CAP, one or more CAP may be automatically executed.

FIG. 4C is a flowchart illustrating an embodiment in which CAP may berun automatically or manually. In various embodiments, the flowchart ofFIG. 4C may include more or fewer blocks, and/or various blocks may becombined or divided into additional blocks. In various embodiments, theoperations and/or processes shown in the flowchart of FIG. 4C anddescribed below may be performed by, for example, CAD systems 148,processing systems 149, device 150, device 250, and/or any otherdevice(s) illustrated in FIGS. 1, 2, and/or 3, and/or any other suitablecomputing device. For example, the operations and/or processes shown inthe flowchart of FIG. 4C may be embodied in one or more software modulesincluding computer executable instructions and executable by one or morehardware processors. For purposes of illustration, the blocks arediscussed below as being performed by computing device 150.

At block 430, the computing device 150 accesses CAP rules that areusable to determine when CAP are run are retrieved, for example, rules408 and/or the rules of FIG. 4B that are stored in one or more rulesdata structures, such as CAP Rules Data Structure 160.

At block 432, the computing device 150 evaluates the CAP rules in orderto determine if one or more CAP should be executed, for example, basedon modality, exam type, clinical indication, ordering physicianpreference, reading radiologist preference, insurance approval, resultsof other CAP, and the like.

If the computing device determines, at block 432, that there is no CAPto run automatically, the computing device 150 optionally accepts inputfrom a radiologist, or other user indicating a CAP to be manually run.Such input from the radiologist may be received by the radiologistproviding, for example, an input to the device 150 (and/or any othersuitable computing device). If the input indicates that no CAP should berun, then no more action occurs within this logic, as indicated by block442.

At block 434, a CAP is run, either because one was automaticallyselected at block 432, or because a manual command was received at block440. In optional block 436, results of the CAP performed may becommunicated to other processes. In one embodiment, the CAP results maybe automatically communicated to various users. In one embodiment, CAPresults may be communicated to a system used to create reports, such asRadiology Information System 140. Example embodiments are discussedherein with reference FIGS. 7A, 7B, and 8.

At block 436 (or block 434 if block 436 is not included), the logicloops back to block 432 to determine whether additional CAP should berun. As discussed above, CAP rules may cause CAP to run based on theresult of one or more other CAP. For example, a rule for executing aparticular CAP may not have been met in a first run of blocks 432 and434, but the rule may be met in a subsequent run of block 432 based onresults of a CAP that was performed at block 434 of the first run.

Example User Interfaces

FIG. 5 illustrates a sample display device (for example, a portion ofone of the computing devices 150 or 250) with status informationregarding CAP that are scheduled, in progress, and/or completed (and/orother statuses). In some embodiments, CAP may require relatively longperiods of time to process. For example, certain CAP use complexcomputer algorithms that require relatively long periods of time toexecute. Additionally, in cases where CAP occurs remotely (for example,by a CAP server in communication via the Internet), communication time(for example, transfer of exam images and/or results) may be increased.

In some instances, users (for example, radiologists) may desire that allapplicable CAP are complete before they view an exam. Thus, in someembodiments the modules 151 are configured to generate one or more userinterfaces (UIs) that indicate status of various CAP. In the example ofFIG. 5, a UI is shown that includes a patient list and statusindications for each CAP associated with a particular exam of thepatient. Thus, in various embodiments, a user may elect to choose examsto read that have completed CAP and/or delay choosing exams whereprocessing is incomplete.

In systems wherein exams are automatically chosen for reading (forexample, downloaded to a particular workstation automatically and/orautomatically prioritized), either on-the-fly or via building worklists, CAP statuses may be utilized. For example, a PACS workstation orother computing device (for example, computing device 150 or 250) mayautomatically retrieve exams for the user to read based on a number offactors, such as CAP completion status, exam status (Stat, routine, andthe like), exam description, exam date, user's specialty, userpreference, and/or any other related criteria. Thus, in someembodiments, the user may have a preference not to have exams stillundergoing CAP (for example, status is not complete) included on aworklist for the user. In another embodiment, the completion status ofCAP may be ignored for exams that have certain characteristics, such asthose marked as STAT, otherwise emergent, and/or have some othercharacteristic. In another embodiment, a result of CAP, such as a resultdesignated as a critical result, may cause a user to be automaticallynotified of the result and/or the exam to be prioritized in the readingqueue.

FIG. 6 illustrates a sample display device (for example, a portion ofone of the computing devices 150 or 250) depicting CAP statusinformation, as well as medical images including notations from one ormore CAP. In various embodiments, the sample UI of FIG. 6 allows users,such as radiologists, viewing exams on a computing device to be aware ofvarious aspects of CAP operations. In one embodiment, available types ofCAP applicable to the exam type are listed with status. In thisembodiment, a user (for example, a doctor) may indicate CAP to beperformed and control which CAP indicators are displayed.

In various embodiments, a user interface such as the UI of FIG. 6 maydisplay one or more of:

-   -   The various CAP available and relevant to the exam being viewed.    -   Which CAP systems have been selected to process the exam, either        because they were automatically or manually chosen.    -   The status of CAP, for example, pending, in progress, complete,        and the like.    -   Which CAP have been run.    -   Which CAP doctors have viewed and/or acknowledged.    -   Which CAP results are/are not in the report.    -   Which CAP have detected an important or critical result.    -   Whether the appropriate manual and/or automatic actions have        been performed for communication of detected important/critical        results.

Results of one or more CAP may include information that may be importantfor one or more users (for example, radiologist, referring doctor, andthe like) to view. For example, in the case of CAD systems, in variousembodiments the results may be one or more indicators that aresuperimposed on images to indicate to the user one or more of:

-   -   The location of a detected abnormality.    -   The “type” of a detected abnormality, for example, aneurysm vs.        stenosis in a vascular analysis CAD system.    -   For each detected abnormality, a level of confidence that the        abnormality is present.

In various embodiments, certain CAP may determine one or more sets ofindicators that may be superimposed on the images. In the embodiment ofFIG. 6, the user has the ability to select indicators for display fromany of one or more CAP that were performed on the displayed image,series, or exam. In the example of FIG. 6, the user has chosen todisplay indicators that show where a Tumor Detection CAD system hasidentified lesions. In the example shown, the indicators comprise acircle and internal arrow centered on the location of a detected lesion.In one embodiment, when the user selects another completed CAP (or atleast partially completed CAP) listed in the GUI, the informationrelated to the selected CAP is displayed, such as indicatorssuperimposed on the images. In one embodiment, the user can includeindicators from multiple CAP concurrently on displayed images. In oneembodiment, the user may click or otherwise select a CAP to cause theresults of the CAP to be displayed.

In the example of FIG. 6, the UI indicates that “Tumor Detection CAD” isboth complete and the results are currently being displayed (black texton a white background vs. the other lines which show white text on ablack background).

The UI further indicates that “3D Registration” is in progress and thatthe exams being registered are the exams dated Aug. 2, 2012, the currentexam being viewed, and the exam of Apr. 5, 2012. In another embodiment,in addition to the dates of the exams being registered, otherinformation about the exams may be displayed, for example, a modality,an exam type, an exam time, and the like. In one embodiment, the usermay hover over or click on an item in the status list in order to viewother information, for example, exam type, modality, exam type, and/orestimated time for completion of the CAP in progress, among otherinformation. The other information may be displayed, for example, in apopup frame or under the status line.

The UI further indicates that the “Change Detection CAD” has beenscheduled, and will be run after another CAP is complete, “3DRegistration” in this example. The example UI of FIG. 6 furtherindicates that the “Brain Volumetrics” CAP is available, but notscheduled.

In one embodiment, the user may click or otherwise select a CAP that hasnot been scheduled to cause it to be scheduled and/or change itspriority with reference to other CAP. In one embodiment, additionalinformation may be displayed, e.g., the estimated time for completion ofthe listed CAP or in indictor showing its completion status, e.g., a bardemonstrating that a cap is 60% completed.

Reporting CAP Results

There is a need to manage how the results of CAP are communicated, forexample via reports of exams and/or other means (for example, automaticcommunication to a doctor interpreting the exam, a doctor who orderedthe exam, a doctor providing care for the patient, an electronic medicalrecord, or a database). In one embodiment, the modules 151 (and/or othersystems that coordinate selection and initiation of various CAP asdiscussed above) are configured to automatically put CAP results in areport associated with an exam. The modules 151 may automatically alerta user (for example, a doctor) if a CAP detects a significantabnormality in an exam that has not yet been viewed. In anotherembodiment, when a CAP detects a result that is designated assignificant or emergent (for example, based on rules stored inComputerized Advanced Processing Rules Data Structure 160) the resultmay be automatically communicated, for example, to one or more of adoctor who ordered the exam, a doctor providing care for the patient, anelectronic medical record, a database, and/or the like. In oneembodiment, automatic communication of a significant or emergent resultdetected by a CAP may occur before the exam has been viewed by a user.In one embodiment, automatic communication of a significant or emergentresult detected by a CAP may occur after the exam has been viewed by auser.

In one embodiment, alerts and/or other actions to be taken based onresults of one or more CAP may be stored in an alert data structure thatcontains rules for providing alerts and/or taking other actions. Forexample, rules may indicate that important or other types of resultsgenerated by CAP result in automatic action, for example automaticalerting of a user or other communication of results. The alert datastructure may include multiple delivery options, such as deliverymediums (for example, email, SMS, phone, etc.), delivery schedules (forexample, only certain alerts may be delivered outside of pre-set workhours), destinations (for example, certain alerts may go to an entiremedical group, while others only go to a referring physician), and/orother similar alert parameters. In one embodiment, the alert datastructure stores results of performed CAP(s) that may be included inalerts, either before or after a report is generated and/or marked asread.

FIG. 7A is a flowchart illustrating an embodiment in which certainresults of CAP are automatically communicated. In various embodiments,the flowchart of FIG. 7A may include more or fewer blocks, and/orvarious blocks may be combined or divided into additional blocks. Invarious embodiments, the operations and/or processes shown in theflowchart of FIG. 7A and described below may be performed by, forexample, CAD systems 148, processing systems 149, device 150, device250, any other device(s) illustrated in FIGS. 1, 2, and/or 3, and/or anyother suitable computing device. For example, the operations and/orprocesses shown in the flowchart of FIG. 7A may be embodied in one ormore software modules including computer executable instructions andexecutable by one or more hardware processors. For purposes ofillustration, the method of FIG. 7A will be described below as performedby the computing device 150.

At block 710, results of a CAP and/or an indication that results of theCAP are available are received by the computing device 150.

Next, at block 712 the received CAP results are evaluated in light ofCAP processing rules to determine if the CAP results are to beautomatically communicated to one or more users, devices, systems, etc.In one example, the CAP processing rules may indicate that onlysignificant results may be communicated automatically (and may includecriteria for what qualifies as a significant result), whereas in anotherexample all results may be automatically communicated, depending onrules configured for individuals, groups, and/or sites.

If the computing device 150 determines, at block 712, that the CAPresults are to be automatically communicated, the method continues toblock 714 wherein CAP communication preferences are retrieved, forexample, from CAP Communication Preferences Data Structure 162. Forexample, CAP communication preferences may indicate that a significantfinding detected by CAP, such as detection of a pneumothorax on a chestx-ray or chest CT scan, is to be treated as a significant findingrequiring immediate communication. Information in the CAP CommunicationsPreferences Data Structure may indicate that significant findings becommunicated automatically to the ordering physician, the hospitalistcurrently caring for the patient, and/or the radiologist current readingcases or on call. Information in the CAP Communications Preferences DataStructure might also include the preferred method of communication setby each user, for example, text, email, phone call, and/or the like.

Moving to block 716, the CAP results are automatically communicatedbased on the preceding determinations, such as to one or more users,devices, systems, etc., via one or more communication mediums, andincluding certain portions of the CAP results possible in customformats. Thus, CAP results may be sent to two different users viadifferent communication mediums (e.g., one via email and another viatext message) including different portions of the CAP results (e.g., allof the report in an email vs. only a summary of the report in a textmessage). In one embodiment, automated communications are automaticallylogged. When it is determined that no results to be automaticallycommunicated, the process stops at block 718.

In various embodiments, the modules 151 may further be configured toprovide one or more of various alerts as an exam is being viewed. Forexample, the modules 151 may be configured to initiate alerts to theuser in response to one or more of:

-   -   User closes an exam or attempts to mark exam as read before all        scheduled CAP is complete.    -   User closes an exam or attempts to mark exam as read without        viewing all CAP results (or CAP results with at least a        threshold importance).    -   User closes an exam or attempts to mark a case as read without        acknowledging CAP results.    -   User attempts to mark report as complete and CAP results are not        included in a report.    -   User attempts to mark report as complete and important or        critical CAP results are not included in a report.    -   User attempts to mark report as complete while critical or other        types of results have not been communicated, for example, to the        ordering physician, or processed for communication has not been        initiated.

FIG. 7B is a flowchart illustrating an embodiment in which results ofCAP are automatically incorporated into reports, such as radiologyreports created by radiologists related to medical imaging exams,utilizing, for example, Radiology Information System 140. In variousembodiments, the flowchart of FIG. 7B may include more or fewer blocks,and/or various blocks may be combined or divided into additional blocks.In various embodiments, the operations and/or processes shown in theflowchart of FIG. 7B and described below may be performed by, forexample, CAD systems 148, processing systems 149, device 150, device250, any other device(s) illustrated in FIGS. 1, 2, and/or 3, and/or anyother suitable computing device. For example, the operations and/orprocesses shown in the flowchart of FIG. 7B may be embodied in one ormore software modules including computer executable instructions andexecutable by one or more hardware processors. For purposes ofillustration, the method of FIG. 7B will be described below as performedby the computing device 150.

Beginning at block 730, results of a CAP and/or an indication thatresults of the CAP are available are received by the computing device150.

At block 732, rules are evaluated to determine whether the CAP resultsshould be incorporated into a medical report and/or other document orfile. These rules may be stored in CAP Rules Data Structure 160. By wayof example, a rule may indicate that only positive CAP results beincluded in the reports. For example, if significant midline shift isdetected by a computer aided diagnosis system, a form of CAP that may beused to evaluate a brain CT, the significant result may be automaticallyincluded in the report. In another example, another rule may indicatethat all CAP results, or some other subset of results that are selectedbased on rule criteria, are automatically incorporated into the report,regardless of the result, such as a CSF volumetric assessment of a brainMRI. Rules may incorporate preferences of individual users, groups,and/or sites. For example, one radiologist may configure the system sothat the results of a particular CAP are automatically incorporated intohis reports, while another might indicate that the CAP results shouldnot be automatically incorporated.

At block 736, the CAP results are incorporated into the report.Alternatively, when it is determined that no CAP results are to beincluded in the report, the process stops at block 738.

FIG. 8 is a flow chart that illustrates an embodiment that operates inrelation to a radiologist creating a report on a medical exam wherethere are related CAP results. In various embodiments, the flowchart ofFIG. 8 may include more or fewer blocks, and/or various blocks may becombined or divided into additional blocks. In various embodiments, theoperations and/or processes shown in the flowchart of FIG. 8 anddescribed below may be performed by, for example, CAD systems 148,processing systems 149, device 150, device 250, any other device(s)illustrated in FIGS. 1, 2, and/or 3, and/or any other suitable computingdevice. For example, the operations and/or processes shown in theflowchart of FIG. 8 may be embodied in one or more software modulesincluding computer executable instructions and executable by one or morehardware processors. For purposes of illustration, the method of FIG. 8will be described below as performed by the computing device 150.

Beginning at block 810, a radiologist or other reader attempts to markthe exam he is reading as “read,” indicating that he has completed hisevaluation of the exam and desires to finalize the report on the exam.

At block 812, the system determines whether or not a significant findingwas detected by a CAP run on the exam. Rules determining which resultsare “significant” may be stored in a data structure, such as CAP RulesData Structure 160. Rules may be set by various users, such asindividual radiologists and/or ordering physicians, and/or by groups ofusers. For example, detection of a subdural hematoma by a CAD processingof a brain CT may be an example of a significant finding.

At block 812, if it is determined that no significant finding wasdetected by CAP associated with the exam, then the radiologist may markthe exam as read at block 814.

Alternatively, at block 812, if it is determined that a significantfinding was detected, then at block 816, the system may determinewhether or not the significant finding is documented in the report, forexample, because it was automatically added by the system or manuallyadded by the radiologist.

If the significant finding is not in the report, then at block 818 theradiologist is notified that the significant finding is not documentedin the report so that he has the opportunity to add the finding to thereport. In various embodiments, the radiologist may be notified by, forexample, a visual, audible, and/or tactile indicator. For example, theradiologist may be prompted by a message or flashing indicator on thedisplay, or an audible alarm. If, at block 816, it is determined thatthe significant finding is in the report, the system proceeds to block820.

At block 820, CAP processing rules are used to determine whether or notthe significant finding should be automatically communicated, forexample, to the physician caring for the patient and/or the physicianwho ordered the imaging exam. If it is determined that there are norules that indicate that the significant finding should be automaticallycommunicated, then at optional block 830 the radiologist is notifiedthat the system is not going to automatically communicate thesignificant finding. At optional block 832, the radiologist may indicatethat he would like the system to communicate the findings, for example,to the physician caring for the patient.

At block 822, performed in preparation for communicating the finding,CAP communications preferences are retrieved, for example, from CAPCommunication Preferences Data Structure 162, to determine the mode ofautomated communication, for example, text, pager, email, phone call,and/or the like.

At block 824, the significant finding is communicated to the designatedand/or indicated user. At optional block 826, the results of theautomated communication may be automatically documented, for example, inthe report and/or another record.

OTHER EMBODIMENTS

Conditional language, such as, among others, “can,” “could,” “might,” or“may,” unless specifically stated otherwise, or otherwise understoodwithin the context as used, is generally intended to convey that certainembodiments include, while other embodiments do not include, certainfeatures, elements and/or steps. Thus, such conditional language is notgenerally intended to imply that features, elements and/or steps are inany way required for one or more embodiments or that one or moreembodiments necessarily include logic for deciding, with or without userinput or prompting, whether these features, elements and/or steps areincluded or are to be performed in any particular embodiment.

Any process descriptions, elements, or blocks in the flow diagramsdescribed herein and/or depicted in the attached figures should beunderstood as potentially representing modules, segments, or portions ofcode which include one or more executable instructions for implementingspecific logical functions or steps in the process. Alternateimplementations are included within the scope of the embodimentsdescribed herein in which elements or functions may be deleted, executedout of order from that shown or discussed, including substantiallyconcurrently or in reverse order, depending on the functionalityinvolved, as would be understood by those skilled in the art.

All of the methods and processes described above may be embodied in, andpartially or fully automated via, software code modules executed by oneor more general purpose computers. For example, the methods describedherein may be performed by an information display computing deviceand/or any other suitable computing device. The methods may be executedon the computing devices in response to execution of softwareinstructions or other executable code read from a tangible computerreadable medium. A tangible computer readable medium is a data storagedevice that can store data that is readable by a computer system.Examples of computer readable mediums include read-only memory,random-access memory, other volatile or non-volatile memory devices,CD-ROMs, magnetic tape, flash drives, and optical data storage devices.

It should be emphasized that many variations and modifications may bemade to the above-described embodiments, the elements of which are to beunderstood as being among other acceptable examples. All suchmodifications and variations are intended to be included herein withinthe scope of this disclosure. The foregoing description details certainembodiments of the invention. It will be appreciated, however, that nomatter how detailed the foregoing appears in text, the invention can bepracticed in many ways. As is also stated above, it should be noted thatthe use of particular terminology when describing certain features oraspects of the invention should not be taken to imply that theterminology is being re-defined herein to be restricted to including anyspecific characteristics of the features or aspects of the inventionwith which that terminology is associated.

What is claimed is:
 1. A computing system comprising: one or morehardware computer processors configured to execute softwareinstructions; and one or more electronic storage devices incommunication with the one or more hardware computer processors andstoring software modules, the software modules comprising softwareinstructions configured for execution by the one or more hardwarecomputer processors in order to cause the computing system to: access,from one or more image storage devices, an image series comprising oneor more medical images; determine a characteristic associated with afirst computerized advanced processing technique applied to the imageseries, the first computerized advanced processing technique includingone selected from a group consisting of volumetric rendering,multiplanar reconstruction, maximum intensity projection, quantitativeanalysis, and computer-aided diagnosis; access a computerized advancedprocessing data structure including rules for executing computerizedadvanced processing techniques based on characteristics of previouslyapplied computerized advanced processing techniques; identify a rulethat corresponds to the determined characteristic associated with thefirst computerized advanced processing technique, the rule indicatingexecution of a second computerized advanced processing technique; andinitiate application of the second computerized advanced processingtechnique to the image series.
 2. The computing system of claim 1,wherein the determined characteristic includes a result of the firstcomputerized advanced processing technique, and wherein the identifiedrule indicates that the second computerized advanced processingtechnique is to be initiated based on the result having a certain valueor range of values.
 3. The computing system of claim 1, wherein thedetermined characteristic includes a status of the first computerizedadvanced processing technique, and wherein the identified rule indicatesthat the second computerized advanced processing technique is to beinitiated only after completion of the first computerized processingtechnique.
 4. The computing system of claim 1, wherein the determinedcharacteristic includes a scheduling of the first computerized advancedprocessing technique, and wherein the identified rule indicates one of:the second computerized advanced processing technique is to be initiatedbefore the first computerized advanced processing technique iscompleted; the second computerized advanced processing technique is tobe initiated after the first computerized advanced processing techniqueis completed; the second computerized advanced processing technique isto be completed before the first computerized advanced processingtechnique is completed; or the second computerized advanced processingtechnique is to be completed after the first computerized advancedprocessing technique is completed.